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Sudoku Solver using a constraint satisfaction approach based on constraint propagation and backtracking and another one based on Relaxation Labeling

Python 100.00%
backpropagation backpropagation-learning-algorithm relaxation-labelling sudoku sudoku-solver

sudokusolver's Introduction

Sudoku Solver

Assignment solved in "Artificial Intelligence: Knowledge Representation and planning" course at Ca'Foscari University, check the report for a project explanation.

Description of the project:

Write a solver for sudoku puzzles using a constraint satisfaction approach based on constraint propagation and backtracking, and one based on Relaxation Labeling. compare the approaches, their strengths and weaknesses. A sudoku puzzle is composed of a square 9x9 board divided into 3 rows and 3 columns of smaller 3x3 boxes. The goal is to fill the board with digits from 1 to 9 such that

  • each number appears only once for each row column and 3x3 box;
  • each row, column, and 3x3 box should containg all 9 digits. The solver should take as input a matrix withwhere empty squares are represented by a standars symbol (e.g., ".", "_", or "0"), while known square should be represented by the corresponding digit (1,...,9).

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